Bootstrapping does not leave one out. As for .632 this is implemented in the rms package's validate and calibrate functions. Note however that any claimed advantages of .632 over the ordinary optimism bootstrap seem to be a result only of the use of a discontinuous improper scoring role (proportion classified correctly). The advantage may vanish when better scoring rules are used. Simulations showing this may be found at http://biostat.mc.vanderbilt.edu/rms
Frank Jin Minming wrote > > Dear All, > > Anyone has some idea how to implement 632 estimator and leave-one out > bootstraping method by using boot package. I know the bootstrap package > has this function, but it sounds not very flexible for my project. > > Thanks, > > Jim > > ______________________________________________ > R-help@ mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/632-estimator-using-boot-package-tp4446720p4446736.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
